grid vs. cloud computing · cloud computing: it on demand capacity utilization most servers have...

© 2008 Parabon Inc. All rights reserved. | 1© 2009 Parabon Computation, Inc. All rights reserved. |

Grid vs. CloudComputing

The similarities and differencesbetween Cloud Computing andExtreme-Scale Computation on Demand®

© 2009 Parabon Computation, Inc. All rights reserved.

Virtualized Data Center

Virtualization bringsnew capabilities to thedata center.

Capacity Utilization


Virtualized Data Center

Virtualization bringsnew capabilities to thedata center.

Grid computing andcloud computing aretwo types of servicesthat benefit fromvirtualization.



Cloud Computing: IT on Demand


Cloud computing enablesself-service provisioning ofvirtual machines.





Goal: “Simplify deployment ofOperating Systems and appservers.”





Goal: “Simplify deployment ofOperating Systems and appservers.”

Characteristics: Smallnumbers of VM allocationsheld for long periods of time(days/months).




Most servers have utilizationrates of just 5-20%; the other80-95% is wasted capacity.1

Cloud provisioning tools andvirtualization greatly improveutilization rates. Even so, mostdata centers have massiveamounts of capacity that goesunused.

[1] Taurus - A Taxonomy of the Actual Utilizationof Real UNIX and Windows Servers, David GHeap, Principal IT Consultant, IBM EnterpriseServer Group, January 2003. http://www-03.ibm.com/servers/library/pdf/taurus.pdf

UNUSED


Grid: Extreme-Scale Computation on Demand®


Grid computing solutionsenable parallel processingof computational tasks, oftenusing idle vs. dedicatedcapacity.





Goals: “Accelerate throughputfrom decades to days orfrom months to minutes.”






“Enable deep computationsthat are otherwise intractable.”






“Enable deep computationsthat are otherwise intractable.”

Characteristics: Largenumbers of work requestsrun for short periods of time(minutes / hours).


Frontier® Grid Services


The Frontier® Grid Platformcan share resources with cloudsolutions to provide a high-performance compute serviceusing otherwise wastedcapacity.




The Frontier® Grid Platformcan share resources with cloudsolutions to provide a high-performance compute serviceusing otherwise wastedcapacity.

The Frontier Grid Servermanages execution of large-scale computational jobsacross hundreds or thousandsof compute nodes.




The Frontier Compute Enginecan be deployed as a small,unobtrusive virtual applianceacross the entire data center.




The Frontier Compute Enginecan be deployed as a small,unobtrusive virtual applianceacross the entire data center.

Frontier uses resources onlywhen its host has excesscapacity. And, it is designed to“back off” when higher priorityprocesses are present.




Computational Work Units

Next, we’ll watch how Frontierexecutes a large-scale job inthe presence of other VMallocations.





A large job comprised of manytasks is launched against theFrontier Grid Service.





The Frontier Grid Serverassigns tasks to computeengines on the grid.





Frontier Compute Engineson hosts with excess capacitybegin executing tasks in turn,and results are returned backto the server.





Capacity utilization in the datacenter increases and the jobfinishes quickly thanks to massparallelization.





Because Frontier runs at lowpriority, other operations, suchas cloud provisioning of newVMs, can proceed as normal.





As the job completes, capacityis freed for use by other jobs.





Our job, which would takeweeks or months on a singlecomputer, finishes in minutesor hours.


Conclusion: Grids ≈ Clouds

Grid and Cloud computing share some common goals:

Deliver computation as a utility Virtualize use of computing resources Eliminate need for dedicated computing resources Dramatically improve computational price-performance

But, the services they provide are fundamentally different:

Cloud – Information Technology (IT) on Demand Grid – Extreme-Scale Computation on Demand®

grid vs. cloud computing · cloud computing: it on demand capacity utilization most servers have...

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